Adaptive control of algae detachment in regulated canal networks

Litrico, Xavier; Belaud, Gilles; Fovet, Ophélie

doi:10.1109/icnsc.2011.5874878

Cited by 5 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mainly driven by the progress in this field, the techniques became also popular for general flow forecasting [31] or even water quality applications [17]. We follow this path in our discussion before highlighting more general, supporting techniques such as data assimilation and uncertainty analysis, as well as the evolution of technical systems.…”

Section: Predictions In Water Systemsmentioning

confidence: 97%

“…However, we would like to address general techniques which typically come along with models in operational applications. The most important ones are aiming at data assimilation [2,16,17,29] and uncertainty analysis. These techniques try to update the inputs, parameters, states, or outputs of a model based on historical observations for improving the lead time accuracy of the model or for providing information of the probable model error.…”

Section: Predictions In Water Systemsmentioning

confidence: 99%

“…Non-structural measures in water systems, such as adjustable structures like gates, pumps, and sluices, are operated in order to keep water levels [9,11,29,31], flows [5,14,24,31], or water quality variables [1,17,18] in a desired state. There are many ways in which these adjustable structures can be controlled.…”

Section: Control Of Water Systemsmentioning

confidence: 99%

“…Several successful implementations of control systems on water systems are described in [21]. In increasing order of information usage, three possible types of control for water systems are feedback control [5,11,18], feed-forward control [17,31], and model predictive control [1,8,9,14,24,29].…”

Section: Control Of Water Systemsmentioning

confidence: 99%

“…These non-linear models are still significantly reduced by using a large spatial discretization. In [38,1,17], the water quantity model is combined with a water quality model. It is clear, however, that ideally the most advanced prediction tools discussed in Section II would be used for providing the predictions.…”

Section: Control Of Water Systemsmentioning

confidence: 99%

See 4 more Smart Citations

Towards integrating water prediction and control technology

Overloop

Negenborn

Schwanenberg

et al. 2011

2011 International Conference on Networking, Sensing and Control

View full text Add to dashboard Cite

Abstract-In most countries, especially in deltas, there is a long tradition in the management of water resource systems, in particular related to structural measures such as the construction of dikes and riverine/coastal hydraulic structures. We discuss how this infrastructure can be supported and managed in order to serve as non-structural measures. Therefore, we present a review about technology for the prediction and control of water resources. This covers techniques for flow and water quality forecasting including modeling and data assimilation as well as its combination with predictive controllers for managing hydraulic structures. These techniques are discussed both from a conceptual and technical perspective. Furthermore, we give an overview about ongoing and future work in this field, which is aimed at integrating the techniques from both the water prediction and the water control community.

show abstract

Section: Predictions In Water Systemsmentioning

confidence: 97%

Section: Predictions In Water Systemsmentioning

confidence: 99%

Section: Control Of Water Systemsmentioning

confidence: 99%

Section: Control Of Water Systemsmentioning

confidence: 99%

Section: Control Of Water Systemsmentioning

confidence: 99%

See 3 more Smart Citations

Towards integrating water prediction and control technology

Overloop

Negenborn

Schwanenberg

et al. 2011

2011 International Conference on Networking, Sensing and Control

View full text Add to dashboard Cite

show abstract

Towards Mechanistic Hydrological Limits: A Literature Synthesis to Improve the Study of Direct Linkages between Sediment Transport and Periphyton Accrual in Gravel-Bed Rivers

Neverman

Death

Fuller

et al. 2018

Environmental Management

View full text Add to dashboard Cite

Altered hydrological, sediment, and nutrient regimes can lead to dramatic increases in periphyton abundance in rivers below impoundments. Flushing flows are a commonly adopted strategy to manage the excess periphyton that can accumulate, but in practice they often prove ineffective. Designing hydrological regimes that include flushing flows may be overlooking key processes in periphyton removal, particularly the role of abrasion and molar action induced by substrate movement. Setting flow targets which aim to initiate substrate movement are likely to improve periphyton removal, but an understanding of the site-specific thresholds for substrate entrainment and periphyton removal is required. Despite decades of entrainment studies accurate and consistent measurement and prediction of substrate entrainment remains elusive, making it challenging to study the relationship between substrate movement and periphyton removal, and to set flow targets. This paper makes a case for using substrate entrainment and transport thresholds as the target metric for flushing flows to manage excess periphyton accrual. This paper critically reviews the determinants of periphyton accrual and associated management methods. This paper also aims to provide a reference for interdisciplinary research on periphyton removal by summarising the geomorphic and hydraulic literature on methods for estimating and measuring substrate entrainment and transport. This will provide a basis for ecologists to identify tools for quantifying entrainment and transport thresholds so they are better placed to explore the direct linkages between phases of sediment transport and periphyton accrual. These linkages need to be identified in order for river managers to set effective flushing flow targets.

show abstract

Model reduction in model predictive control of combined water quantity and quality in open channels

Overloop

Giesen

2013

Environmental Modelling & Software

View full text Add to dashboard Cite

Adaptive control of algae detachment in regulated canal networks

Cited by 5 publications

References 14 publications

Towards integrating water prediction and control technology

Towards integrating water prediction and control technology

Towards Mechanistic Hydrological Limits: A Literature Synthesis to Improve the Study of Direct Linkages between Sediment Transport and Periphyton Accrual in Gravel-Bed Rivers

Model reduction in model predictive control of combined water quantity and quality in open channels

Contact Info

Product

Resources

About